Merge branch 'v0.6.3.post1-dev'

.github/workflows/remove_label_not_ready_comment.yml

-name: Remove ready Label on notready Comment
-
-on:
-  issue_comment:
-    types: [created]
-
-jobs:
-  add-ready-label:
-    runs-on: ubuntu-latest
-    if: github.event.issue.pull_request && contains(github.event.comment.body, '/notready')
-    steps:
-        -   name: Remove ready label
-            uses: actions/github-script@v5
-            with:
-                script: |
-                    github.rest.issues.removeLabel({
-                        owner: context.repo.owner,
-                        repo: context.repo.repo,
-                        issue_number: context.issue.number,
-                        name: 'ready'
-                    })
-            env:
-                GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/ruff.yml

@@ -17,18 +17,18 @@ jobs:
       matrix:
         python-version: ["3.8", "3.9", "3.10", "3.11", "3.12"]
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v4
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v5
       with:
         python-version: ${{ matrix.python-version }}
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
-        pip install ruff==0.1.5 codespell==2.3.0 tomli==2.0.1 isort==5.13.2
+        pip install -r requirements-lint.txt
     - name: Analysing the code with ruff
       run: |
-        ruff .
+        ruff check .
     - name: Spelling check with codespell
       run: |
         codespell --toml pyproject.toml

.github/workflows/scripts/build.sh

 #!/bin/bash
+set -eux
 
 python_executable=python$1
 cuda_home=/usr/local/cuda-$2
@@ -8,12 +9,15 @@ PATH=${cuda_home}/bin:$PATH
 LD_LIBRARY_PATH=${cuda_home}/lib64:$LD_LIBRARY_PATH
 
 # Install requirements
-$python_executable -m pip install wheel packaging
-$python_executable -m pip install -r requirements-cuda.txt
+$python_executable -m pip install -r requirements-build.txt -r requirements-cuda.txt
 
 # Limit the number of parallel jobs to avoid OOM
 export MAX_JOBS=1
 # Make sure release wheels are built for the following architectures
 export TORCH_CUDA_ARCH_LIST="7.0 7.5 8.0 8.6 8.9 9.0+PTX"
+export VLLM_FA_CMAKE_GPU_ARCHES="80-real;90-real"
+
+bash tools/check_repo.sh
+
 # Build
 $python_executable setup.py bdist_wheel --dist-dir=dist

.github/workflows/yapf.yml

@@ -16,9 +16,9 @@ jobs:
       matrix:
         python-version: ["3.8", "3.9", "3.10", "3.11", "3.12"]
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v4
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v5
       with:
         python-version: ${{ matrix.python-version }}
     - name: Install dependencies

.gitignore

-# vllm commit id, generated by setup.py
-vllm/commit_id.py
+# version file generated by setuptools-scm
+/vllm/_version.py
+
+# vllm-flash-attn built from source
+vllm/vllm_flash_attn/
 
 # Byte-compiled / optimized / DLL files
 __pycache__/
@@ -12,6 +15,8 @@ __pycache__/
 # Distribution / packaging
 .Python
 build/
+cmake-build-*/
+CMakeUserPresets.json
 develop-eggs/
 dist/
 downloads/
@@ -28,6 +33,7 @@ share/python-wheels/
 .installed.cfg
 *.egg
 MANIFEST
+/.deps/
 
 # PyInstaller
 #  Usually these files are written by a python script from a template
@@ -87,6 +93,9 @@ target/
 profile_default/
 ipython_config.py
 
+# generated files
+**/generated/**
+
 # pyenv
 #   For a library or package, you might want to ignore these files since the code is
 #   intended to run in multiple environments; otherwise, check them in:
@@ -189,4 +198,7 @@ _build/
 hip_compat.h
 
 # Benchmark dataset
-*.json
+benchmarks/*.json
+
+# Linting
+actionlint

.readthedocs.yaml

@@ -13,10 +13,10 @@ sphinx:
    fail_on_warning: true
 
 # If using Sphinx, optionally build your docs in additional formats such as PDF
-formats:
-   - pdf
+formats: []
 
 # Optionally declare the Python requirements required to build your docs
 python:
    install:
    - requirements: docs/requirements-docs.txt
+

CMakeLists.txt

-cmake_minimum_required(VERSION 3.21)
+cmake_minimum_required(VERSION 3.26)
 
+# When building directly using CMake, make sure you run the install step
+# (it places the .so files in the correct location).
+#
+# Example:
+# mkdir build && cd build
+# cmake -G Ninja -DVLLM_PYTHON_EXECUTABLE=`which python3` -DCMAKE_INSTALL_PREFIX=.. ..
+# cmake --build . --target install
+#
+# If you want to only build one target, make sure to install it manually:
+# cmake --build . --target _C
+# cmake --install . --component _C
 project(vllm_extensions LANGUAGES CXX)
 
 # CUDA by default, can be overridden by using -DVLLM_TARGET_DEVICE=... (used by setup.py)
@@ -12,6 +23,14 @@ message(STATUS "Target device: ${VLLM_TARGET_DEVICE}")
 
 include(${CMAKE_CURRENT_LIST_DIR}/cmake/utils.cmake)
 add_compile_options(-w)
+
+
+# Suppress potential warnings about unused manually-specified variables
+set(ignoreMe "${VLLM_PYTHON_PATH}")
+
+# Prevent installation of dependencies (cutlass) by default.
+install(CODE "set(CMAKE_INSTALL_LOCAL_ONLY TRUE)" ALL_COMPONENTS)
+
 #
 # Supported python versions.  These versions will be searched in order, the
 # first match will be selected.  These should be kept in sync with setup.py.
@@ -69,19 +88,6 @@ endif()
 find_package(Torch REQUIRED)
 
 #
-# Add the `default` target which detects which extensions should be
-# built based on platform/architecture.  This is the same logic that
-# setup.py uses to select which extensions should be built and should
-# be kept in sync.
-#
-# The `default` target makes direct use of cmake easier since knowledge
-# of which extensions are supported has been factored in, e.g.
-#
-# mkdir build && cd build
-# cmake -G Ninja -DVLLM_PYTHON_EXECUTABLE=`which python3` -DCMAKE_LIBRARY_OUTPUT_DIRECTORY=../vllm ..
-# cmake --build . --target default
-#
-add_custom_target(default)
 message(STATUS "Enabling core extension.")
 
 # Define _core_C extension
@@ -99,8 +105,6 @@ define_gpu_extension_target(
   USE_SABI 3
   WITH_SOABI)
 
-add_dependencies(default _core_C)
-
 #
 # Forward the non-CUDA device extensions to external CMake scripts.
 #
@@ -143,15 +147,33 @@ else()
   message(FATAL_ERROR "Can't find CUDA or HIP installation.")
 endif()
 
-#
-# Override the GPU architectures detected by cmake/torch and filter them by
-# the supported versions for the current language.
-# The final set of arches is stored in `VLLM_GPU_ARCHES`.
-#
-override_gpu_arches(VLLM_GPU_ARCHES
-  ${VLLM_GPU_LANG}
-  "${${VLLM_GPU_LANG}_SUPPORTED_ARCHS}")
-  
+
+if(VLLM_GPU_LANG STREQUAL "CUDA")
+  #
+  # For cuda we want to be able to control which architectures we compile for on 
+  # a per-file basis in order to cut down on compile time. So here we extract
+  # the set of architectures we want to compile for and remove the from the 
+  # CMAKE_CUDA_FLAGS so that they are not applied globally.
+  #
+  clear_cuda_arches(CUDA_ARCH_FLAGS)
+  extract_unique_cuda_archs_ascending(CUDA_ARCHS "${CUDA_ARCH_FLAGS}")
+  message(STATUS "CUDA target architectures: ${CUDA_ARCHS}")
+  # Filter the target architectures by the supported supported archs
+  # since for some files we will build for all CUDA_ARCHS.
+  cuda_archs_loose_intersection(CUDA_ARCHS 
+    "${CUDA_SUPPORTED_ARCHS}" "${CUDA_ARCHS}")
+  message(STATUS "CUDA supported target architectures: ${CUDA_ARCHS}")
+else()
+  #
+  # For other GPU targets override the GPU architectures detected by cmake/torch
+  # and filter them by the supported versions for the current language.
+  # The final set of arches is stored in `VLLM_GPU_ARCHES`.
+  #
+  override_gpu_arches(VLLM_GPU_ARCHES
+    ${VLLM_GPU_LANG}
+    "${${VLLM_GPU_LANG}_SUPPORTED_ARCHS}")
+endif()
+
 #
 # Query torch for additional GPU compilation flags for the given
 # `VLLM_GPU_LANG`.
@@ -166,6 +188,17 @@ if(NVCC_THREADS AND VLLM_GPU_LANG STREQUAL "CUDA")
   list(APPEND VLLM_GPU_FLAGS "--threads=${NVCC_THREADS}")
 endif()
 
+
+#
+# Use FetchContent for C++ dependencies that are compiled as part of vLLM's build process.
+# Configure it to place files in vllm/.deps, in order to play nicely with sccache.
+#
+include(FetchContent)
+get_filename_component(PROJECT_ROOT_DIR "${CMAKE_CURRENT_SOURCE_DIR}" ABSOLUTE)
+file(MAKE_DIRECTORY "${FETCHCONTENT_BASE_DIR}")
+set(FETCHCONTENT_BASE_DIR "${PROJECT_ROOT_DIR}/.deps")
+message(STATUS "FetchContent base directory: ${FETCHCONTENT_BASE_DIR}")
+
 #
 # Define other extension targets
 #
@@ -184,9 +217,9 @@ set(VLLM_EXT_SRC
   "csrc/opt/transpose_kernels.cu"
   "csrc/opt/activation_kernels_opt.cu"
   "csrc/attention/attention_kernels_opt.cu"
+  "csrc/attention/attention_kernels_opt_tc.cu"
   "csrc/opt/layernorm_kernels_opt.cu"
-  "csrc/quantization/squeezellm/quant_cuda_kernel.cu"
-  "csrc/quantization/gptq/q_gemm.cu"
+  # "csrc/quantization/gptq/q_gemm.cu"
   "csrc/quantization/compressed_tensors/int8_quant_kernels.cu"
   # "csrc/quantization/fp8/common.cu"
   "csrc/cuda_utils_kernels.cu"
@@ -195,46 +228,188 @@ set(VLLM_EXT_SRC
   "csrc/torch_bindings.cpp")
 
 if(VLLM_GPU_LANG STREQUAL "CUDA")
-  include(FetchContent)
   SET(CUTLASS_ENABLE_HEADERS_ONLY ON CACHE BOOL "Enable only the header library")
+
+  # Set CUTLASS_REVISION manually -- its revision detection doesn't work in this case.
+  set(CUTLASS_REVISION "v3.5.1" CACHE STRING "CUTLASS revision to use")
+
   FetchContent_Declare(
         cutlass
         GIT_REPOSITORY https://github.com/nvidia/cutlass.git
-        # CUTLASS 3.5.1
-        GIT_TAG 06b21349bcf6ddf6a1686a47a137ad1446579db9 
+        GIT_TAG v3.5.1
         GIT_PROGRESS TRUE
+
+        # Speed up CUTLASS download by retrieving only the specified GIT_TAG instead of the history.
+        # Important: If GIT_SHALLOW is enabled then GIT_TAG works only with branch names and tags.
+        # So if the GIT_TAG above is updated to a commit hash, GIT_SHALLOW must be set to FALSE
+        GIT_SHALLOW TRUE
   )
   FetchContent_MakeAvailable(cutlass)
 
   list(APPEND VLLM_EXT_SRC
+    "csrc/mamba/mamba_ssm/selective_scan_fwd.cu"
+    "csrc/mamba/causal_conv1d/causal_conv1d.cu"
     "csrc/quantization/aqlm/gemm_kernels.cu"
     "csrc/quantization/awq/gemm_kernels.cu"
-    "csrc/quantization/marlin/dense/marlin_cuda_kernel.cu"
-    "csrc/quantization/marlin/sparse/marlin_24_cuda_kernel.cu"
-    "csrc/quantization/marlin/qqq/marlin_qqq_gemm_kernel.cu"
-    "csrc/quantization/gptq_marlin/gptq_marlin.cu"
-    "csrc/quantization/gptq_marlin/gptq_marlin_repack.cu"
-    "csrc/quantization/gptq_marlin/awq_marlin_repack.cu"
-    "csrc/quantization/fp8/fp8_marlin.cu"
+    "csrc/quantization/gguf/gguf_kernel.cu"
     "csrc/custom_all_reduce.cu"
-    "csrc/quantization/cutlass_w8a8/scaled_mm_entry.cu"
-    "csrc/quantization/cutlass_w8a8/scaled_mm_c2x.cu"
-    "csrc/quantization/cutlass_w8a8/scaled_mm_c3x.cu")
+    "csrc/permute_cols.cu"
+    "csrc/quantization/cutlass_w8a8/scaled_mm_entry.cu")
+
+  set_gencode_flags_for_srcs(
+    SRCS "${VLLM_EXT_SRC}"
+    CUDA_ARCHS "${CUDA_ARCHS}")
+
+  # Only build Marlin kernels if we are building for at least some compatible archs.
+  # Keep building Marlin for 9.0 as there are some group sizes and shapes that
+  # are not supported by Machete yet.
+  cuda_archs_loose_intersection(MARLIN_ARCHS "8.0;8.6;8.9;9.0" ${CUDA_ARCHS})
+  if (MARLIN_ARCHS)
+    set(MARLIN_SRCS 
+       "csrc/quantization/fp8/fp8_marlin.cu"
+       "csrc/quantization/marlin/dense/marlin_cuda_kernel.cu"
+       "csrc/quantization/marlin/sparse/marlin_24_cuda_kernel.cu"
+       "csrc/quantization/marlin/qqq/marlin_qqq_gemm_kernel.cu"
+       "csrc/quantization/gptq_marlin/gptq_marlin.cu"
+       "csrc/quantization/gptq_marlin/gptq_marlin_repack.cu"
+       "csrc/quantization/gptq_marlin/awq_marlin_repack.cu")
+    set_gencode_flags_for_srcs(
+      SRCS "${MARLIN_SRCS}"
+      CUDA_ARCHS "${MARLIN_ARCHS}")
+    list(APPEND VLLM_EXT_SRC "${MARLIN_SRCS}")
+    message(STATUS "Building Marlin kernels for archs: ${MARLIN_ARCHS}")
+  else()
+    message(STATUS "Not building Marlin kernels as no compatible archs found"
+                   "in CUDA target architectures")
+  endif()
 
   #
-  # The CUTLASS kernels for Hopper require sm90a to be enabled.
-  # This is done via the below gencode option, BUT that creates kernels for both sm90 and sm90a.
-  # That adds an extra 17MB to compiled binary, so instead we selectively enable it.
-  if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0)
-    set_source_files_properties(
-          "csrc/quantization/cutlass_w8a8/scaled_mm_c3x.cu"
-          PROPERTIES
-          COMPILE_FLAGS
-          "-gencode arch=compute_90a,code=sm_90a")
+  # The cutlass_scaled_mm kernels for Hopper (c3x, i.e. CUTLASS 3.x) require
+  # CUDA 12.0 or later (and only work on Hopper, 9.0/9.0a for now).
+  cuda_archs_loose_intersection(SCALED_MM_3X_ARCHS "9.0;9.0a" "${CUDA_ARCHS}")
+  if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0 AND SCALED_MM_3X_ARCHS)
+    set(SRCS "csrc/quantization/cutlass_w8a8/scaled_mm_c3x.cu")
+    set_gencode_flags_for_srcs(
+      SRCS "${SRCS}"
+      CUDA_ARCHS "${SCALED_MM_3X_ARCHS}")
+    list(APPEND VLLM_EXT_SRC "${SRCS}")
+    list(APPEND VLLM_GPU_FLAGS "-DENABLE_SCALED_MM_C3X=1")
+    message(STATUS "Building scaled_mm_c3x for archs: ${SCALED_MM_3X_ARCHS}")
+  else()
+    if (NOT ${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0 AND SCALED_MM_3X_ARCHS)
+      message(STATUS "Not building scaled_mm_c3x as CUDA Compiler version is "
+                     "not >= 12.0, we recommend upgrading to CUDA 12.0 or "
+                     "later if you intend on running FP8 quantized models on "
+                     "Hopper.")
+    else()
+      message(STATUS "Not building scaled_mm_c3x as no compatible archs found "
+                     "in CUDA target architectures")
+    endif()
+
+    # clear SCALED_MM_3X_ARCHS so the scaled_mm_c2x kernels know we didn't 
+    # build any 3x kernels
+    set(SCALED_MM_3X_ARCHS)
   endif()
 
+  #
+  # For the cutlass_scaled_mm kernels we want to build the c2x (CUTLASS 2.x)
+  # kernels for the remaining archs that are not already built for 3x.
+  cuda_archs_loose_intersection(SCALED_MM_2X_ARCHS 
+    "7.5;8.0;8.6;8.9;9.0" "${CUDA_ARCHS}")
+  # subtract out the archs that are already built for 3x
+  list(REMOVE_ITEM SCALED_MM_2X_ARCHS ${SCALED_MM_3X_ARCHS})
+  if (SCALED_MM_2X_ARCHS)
+    set(SRCS "csrc/quantization/cutlass_w8a8/scaled_mm_c2x.cu")
+    set_gencode_flags_for_srcs(
+      SRCS "${SRCS}"
+      CUDA_ARCHS "${SCALED_MM_2X_ARCHS}")
+    list(APPEND VLLM_EXT_SRC "${SRCS}")
+    list(APPEND VLLM_GPU_FLAGS "-DENABLE_SCALED_MM_C2X=1")
+    message(STATUS "Building scaled_mm_c2x for archs: ${SCALED_MM_2X_ARCHS}")
+  else()
+    if (SCALED_MM_3X_ARCHS)
+      message(STATUS "Not building scaled_mm_c2x as all archs are already built"
+                     " for and covered by scaled_mm_c3x")
+    else()
+      message(STATUS "Not building scaled_mm_c2x as no compatible archs found "
+                    "in CUDA target architectures")
+    endif()
+  endif()
+
+
+  #
+  # Machete kernels
+
+  # The machete kernels only work on hopper and require CUDA 12.0 or later.
+  # Only build Machete kernels if we are building for something compatible with sm90a
+  cuda_archs_loose_intersection(MACHETE_ARCHS "9.0a" "${CUDA_ARCHS}")
+  if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0 AND MACHETE_ARCHS)
+    #
+    # For the Machete kernels we automatically generate sources for various 
+    # preselected input type pairs and schedules.
+    # Generate sources:
+    set(MACHETE_GEN_SCRIPT 
+      ${CMAKE_CURRENT_SOURCE_DIR}/csrc/quantization/machete/generate.py)
+    file(MD5 ${MACHETE_GEN_SCRIPT} MACHETE_GEN_SCRIPT_HASH)
+
+    message(STATUS "Machete generation script hash: ${MACHETE_GEN_SCRIPT_HASH}")
+    message(STATUS "Last run machete generate script hash: $CACHE{MACHETE_GEN_SCRIPT_HASH}")
+
+    if (NOT DEFINED CACHE{MACHETE_GEN_SCRIPT_HASH}
+        OR NOT $CACHE{MACHETE_GEN_SCRIPT_HASH} STREQUAL ${MACHETE_GEN_SCRIPT_HASH})
+      execute_process(
+        COMMAND ${CMAKE_COMMAND} -E env 
+        PYTHONPATH=${CMAKE_CURRENT_SOURCE_DIR}/csrc/cutlass_extensions/:${CUTLASS_DIR}/python/:${VLLM_PYTHON_PATH}:$PYTHONPATH 
+          ${Python_EXECUTABLE} ${MACHETE_GEN_SCRIPT}
+        RESULT_VARIABLE machete_generation_result
+        OUTPUT_VARIABLE machete_generation_output
+        OUTPUT_FILE ${CMAKE_CURRENT_BINARY_DIR}/machete_generation.log
+        ERROR_FILE ${CMAKE_CURRENT_BINARY_DIR}/machete_generation.log
+      )
+
+      if (NOT machete_generation_result EQUAL 0)
+        message(FATAL_ERROR "Machete generation failed."
+                            " Result: \"${machete_generation_result}\"" 
+                            "\nCheck the log for details: "
+                            "${CMAKE_CURRENT_BINARY_DIR}/machete_generation.log")
+      else()
+        set(MACHETE_GEN_SCRIPT_HASH ${MACHETE_GEN_SCRIPT_HASH} 
+            CACHE STRING "Last run machete generate script hash" FORCE)
+        message(STATUS "Machete generation completed successfully.")
+      endif()
+    else()
+      message(STATUS "Machete generation script has not changed, skipping generation.")
+    endif()
+
+    # Add machete generated sources
+    file(GLOB MACHETE_GEN_SOURCES "csrc/quantization/machete/generated/*.cu")
+    list(APPEND VLLM_EXT_SRC ${MACHETE_GEN_SOURCES})
+
+    # forward compatible
+    set_gencode_flags_for_srcs(
+      SRCS "${MACHETE_GEN_SOURCES}"
+      CUDA_ARCHS "${MACHETE_ARCHS}")
+
+    list(APPEND VLLM_EXT_SRC
+      csrc/quantization/machete/machete_pytorch.cu)
+
+    message(STATUS "Building Machete kernels for archs: ${MACHETE_ARCHS}")
+  else()
+    if (NOT ${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0 
+        AND MACHETE_ARCHS)
+      message(STATUS "Not building Machete kernels as CUDA Compiler version is "
+                     "not >= 12.0, we recommend upgrading to CUDA 12.0 or "
+                     "later if you intend on running w4a16 quantized models on "
+                     "Hopper.")
+    else()
+      message(STATUS "Not building Machete kernels as no compatible archs "
+                     "found in CUDA target architectures")
+    endif()
+  endif()
+# if CUDA endif
 endif()
 
+message(STATUS "Enabling C extension.")
 define_gpu_extension_target(
   _C
   DESTINATION vllm
@@ -246,6 +421,12 @@ define_gpu_extension_target(
   USE_SABI 3
   WITH_SOABI)
 
+# If CUTLASS is compiled on NVCC >= 12.5, it by default uses 
+# cudaGetDriverEntryPointByVersion as a wrapper to avoid directly calling the 
+# driver API. This causes problems when linking with earlier versions of CUDA.
+# Setting this variable sidesteps the issue by calling the driver directly.
+target_compile_definitions(_C PRIVATE CUTLASS_ENABLE_DIRECT_CUDA_DRIVER_CALL=1)
+
 #
 # _moe_C extension
 #
@@ -254,6 +435,36 @@ set(VLLM_MOE_EXT_SRC
   "csrc/moe/torch_bindings.cpp"
   "csrc/moe/topk_softmax_kernels.cu")
 
+set_gencode_flags_for_srcs(
+  SRCS "${VLLM_MOE_EXT_SRC}"
+  CUDA_ARCHS "${CUDA_ARCHS}")
+
+if(VLLM_GPU_LANG STREQUAL "CUDA")
+  cuda_archs_loose_intersection(MARLIN_MOE_ARCHS "8.0;8.6;8.9;9.0" "${CUDA_ARCHS}")
+  if (MARLIN_MOE_ARCHS)
+    set(MARLIN_MOE_SRC
+        "csrc/moe/marlin_kernels/marlin_moe_kernel.h"
+        "csrc/moe/marlin_kernels/marlin_moe_kernel_ku4b8.h"
+        "csrc/moe/marlin_kernels/marlin_moe_kernel_ku4b8.cu"
+        "csrc/moe/marlin_kernels/marlin_moe_kernel_ku8b128.h"
+        "csrc/moe/marlin_kernels/marlin_moe_kernel_ku8b128.cu"
+        "csrc/moe/marlin_kernels/marlin_moe_kernel_ku4.h"
+        "csrc/moe/marlin_kernels/marlin_moe_kernel_ku4.cu"
+        "csrc/moe/marlin_moe_ops.cu")
+
+    set_gencode_flags_for_srcs(
+      SRCS "${MARLIN_MOE_SRC}"
+      CUDA_ARCHS "${MARLIN_MOE_ARCHS}")
+
+    list(APPEND VLLM_MOE_EXT_SRC "${MARLIN_MOE_SRC}")
+    message(STATUS "Building Marlin MOE kernels for archs: ${MARLIN_MOE_ARCHS}")
+  else()
+    message(STATUS "Not building Marlin MOE kernels as no compatible archs found"
+                   "in CUDA target architectures")
+  endif()
+endif()
+
+message(STATUS "Enabling moe extension.")
 define_gpu_extension_target(
   _moe_C
   DESTINATION vllm
@@ -264,13 +475,102 @@ define_gpu_extension_target(
   USE_SABI 3
   WITH_SOABI)
 
+#[[  
+if(VLLM_GPU_LANG STREQUAL "HIP")
+  #
+  # _rocm_C extension
+  #
+  set(VLLM_ROCM_EXT_SRC
+    "csrc/rocm/torch_bindings.cpp"
+    "csrc/rocm/attention.cu")
+
+  define_gpu_extension_target(
+    _rocm_C
+    DESTINATION vllm
+    LANGUAGE ${VLLM_GPU_LANG}
+    SOURCES ${VLLM_ROCM_EXT_SRC}
+    COMPILE_FLAGS ${VLLM_GPU_FLAGS}
+    ARCHITECTURES ${VLLM_GPU_ARCHES}
+    USE_SABI 3
+    WITH_SOABI)
+endif()
+]]
+
+# vllm-flash-attn currently only supported on CUDA
+if (NOT VLLM_TARGET_DEVICE STREQUAL "cuda")
+  return()
+endif ()
 
+# vLLM flash attention requires VLLM_GPU_ARCHES to contain the set of target  
+# arches in the CMake syntax (75-real, 89-virtual, etc), since we clear the 
+# arches in the CUDA case (and instead set the gencodes on a per file basis) 
+# we need to manually set VLLM_GPU_ARCHES here.
+if(VLLM_GPU_LANG STREQUAL "CUDA")
+  foreach(_ARCH ${CUDA_ARCHS})
+    string(REPLACE "." "" _ARCH "${_ARCH}")
+    list(APPEND VLLM_GPU_ARCHES "${_ARCH}-real")
+  endforeach()
+endif()
 
-if(VLLM_GPU_LANG STREQUAL "CUDA" OR VLLM_GPU_LANG STREQUAL "HIP")
-  message(STATUS "Enabling C extension.")
-  add_dependencies(default _C)
+#
+# Build vLLM flash attention from source
+#
+# IMPORTANT: This has to be the last thing we do, because vllm-flash-attn uses the same macros/functions as vLLM.
+# Because functions all belong to the global scope, vllm-flash-attn's functions overwrite vLLMs.
+# They should be identical but if they aren't, this is a massive footgun.
+#
+# The vllm-flash-attn install rules are nested under vllm to make sure the library gets installed in the correct place.
+# To only install vllm-flash-attn, use --component vllm_flash_attn_c.
+# If no component is specified, vllm-flash-attn is still installed.
 
-  message(STATUS "Enabling moe extension.")
-  add_dependencies(default _moe_C)
+# If VLLM_FLASH_ATTN_SRC_DIR is set, vllm-flash-attn is installed from that directory instead of downloading.
+# This is to enable local development of vllm-flash-attn within vLLM.
+# It can be set as an environment variable or passed as a cmake argument.
+# The environment variable takes precedence.
+if (DEFINED ENV{VLLM_FLASH_ATTN_SRC_DIR})
+  set(VLLM_FLASH_ATTN_SRC_DIR $ENV{VLLM_FLASH_ATTN_SRC_DIR})
+endif()
 
+if(VLLM_FLASH_ATTN_SRC_DIR)
+  FetchContent_Declare(vllm-flash-attn SOURCE_DIR ${VLLM_FLASH_ATTN_SRC_DIR})
+#[[ 
+else()
+  FetchContent_Declare(
+          vllm-flash-attn
+          GIT_REPOSITORY https://github.com/vllm-project/flash-attention.git
+          GIT_TAG 013f0c4fc47e6574060879d9734c1df8c5c273bd
+          GIT_PROGRESS TRUE
+  )
+]]
 endif()
+
+# Set the parent build flag so that the vllm-flash-attn library does not redo compile flag and arch initialization.
+set(VLLM_PARENT_BUILD ON)
+
+#[[ 
+# Ensure the vllm/vllm_flash_attn directory exists before installation
+install(CODE "file(MAKE_DIRECTORY \"\${CMAKE_INSTALL_PREFIX}/vllm/vllm_flash_attn\")" COMPONENT vllm_flash_attn_c)
+
+# Make sure vllm-flash-attn install rules are nested under vllm/
+install(CODE "set(CMAKE_INSTALL_LOCAL_ONLY FALSE)" COMPONENT vllm_flash_attn_c)
+install(CODE "set(OLD_CMAKE_INSTALL_PREFIX \"\${CMAKE_INSTALL_PREFIX}\")" COMPONENT vllm_flash_attn_c)
+install(CODE "set(CMAKE_INSTALL_PREFIX \"\${CMAKE_INSTALL_PREFIX}/vllm/\")" COMPONENT vllm_flash_attn_c)
+
+# Fetch the vllm-flash-attn library
+FetchContent_MakeAvailable(vllm-flash-attn)
+message(STATUS "vllm-flash-attn is available at ${vllm-flash-attn_SOURCE_DIR}")
+
+# Restore the install prefix
+install(CODE "set(CMAKE_INSTALL_PREFIX \"\${OLD_CMAKE_INSTALL_PREFIX}\")" COMPONENT vllm_flash_attn_c)
+install(CODE "set(CMAKE_INSTALL_LOCAL_ONLY TRUE)" COMPONENT vllm_flash_attn_c)
+
+# Copy over the vllm-flash-attn python files
+install(
+        DIRECTORY ${vllm-flash-attn_SOURCE_DIR}/vllm_flash_attn/
+        DESTINATION vllm/vllm_flash_attn
+        COMPONENT vllm_flash_attn_c
+        FILES_MATCHING PATTERN "*.py"
+)
+
+# Nothing after vllm-flash-attn, see comment about macros above
+]]
\ No newline at end of file

CODE_OF_CONDUCT.md

+
+# vLLM Code of Conduct
+
+## Our Pledge
+
+We as members, contributors, and leaders pledge to make participation in our
+community a harassment-free experience for everyone, regardless of age, body
+size, visible or invisible disability, ethnicity, sex characteristics, gender
+identity and expression, level of experience, education, socioeconomic status,
+nationality, personal appearance, race, caste, color, religion, or sexual
+identity and orientation.
+
+We pledge to act and interact in ways that contribute to an open, welcoming,
+diverse, inclusive, and healthy community.
+
+## Our Standards
+
+Examples of behavior that contributes to a positive environment for our
+community include:
+
+* Demonstrating empathy and kindness toward other people
+* Being respectful of differing opinions, viewpoints, and experiences
+* Giving and gracefully accepting constructive feedback
+* Accepting responsibility and apologizing to those affected by our mistakes,
+  and learning from the experience
+* Focusing on what is best not just for us as individuals, but for the overall
+  community
+
+Examples of unacceptable behavior include:
+
+* The use of sexualized language or imagery, and sexual attention or advances of
+  any kind
+* Trolling, insulting or derogatory comments, and personal or political attacks
+* Public or private harassment
+* Publishing others' private information, such as a physical or email address,
+  without their explicit permission
+* Other conduct which could reasonably be considered inappropriate in a
+  professional setting
+
+## Enforcement Responsibilities
+
+Community leaders are responsible for clarifying and enforcing our standards of
+acceptable behavior and will take appropriate and fair corrective action in
+response to any behavior that they deem inappropriate, threatening, offensive,
+or harmful.
+
+Community leaders have the right and responsibility to remove, edit, or reject
+comments, commits, code, wiki edits, issues, and other contributions that are
+not aligned to this Code of Conduct, and will communicate reasons for moderation
+decisions when appropriate.
+
+## Scope
+
+This Code of Conduct applies within all community spaces, and also applies when
+an individual is officially representing the community in public spaces.
+Examples of representing our community include using an official email address,
+posting via an official social media account, or acting as an appointed
+representative at an online or offline/IRL event.
+
+## Enforcement
+
+Instances of abusive, harassing, or otherwise unacceptable behavior may be
+reported to the community leaders responsible for enforcement in the #code-of-conduct
+channel in the [vLLM Discord](https://discord.com/invite/jz7wjKhh6g).
+All complaints will be reviewed and investigated promptly and fairly.
+
+All community leaders are obligated to respect the privacy and security of the
+reporter of any incident.
+
+## Enforcement Guidelines
+
+Community leaders will follow these Community Impact Guidelines in determining
+the consequences for any action they deem in violation of this Code of Conduct:
+
+### 1. Correction
+
+**Community Impact**: Use of inappropriate language or other behavior deemed
+unprofessional or unwelcome in the community.
+
+**Consequence**: A private, written warning from community leaders, providing
+clarity around the nature of the violation and an explanation of why the
+behavior was inappropriate. A public apology may be requested.
+
+### 2. Warning
+
+**Community Impact**: A violation through a single incident or series of
+actions.
+
+**Consequence**: A warning with consequences for continued behavior. No
+interaction with the people involved, including unsolicited interaction with
+those enforcing the Code of Conduct, for a specified period of time. This
+includes avoiding interactions in community spaces as well as external channels
+like social media. Violating these terms may lead to a temporary or permanent
+ban.
+
+### 3. Temporary Ban
+
+**Community Impact**: A serious violation of community standards, including
+sustained inappropriate behavior.
+
+**Consequence**: A temporary ban from any sort of interaction or public
+communication with the community for a specified period of time. No public or
+private interaction with the people involved, including unsolicited interaction
+with those enforcing the Code of Conduct, is allowed during this period.
+Violating these terms may lead to a permanent ban.
+
+### 4. Permanent Ban
+
+**Community Impact**: Demonstrating a pattern of violation of community
+standards, including sustained inappropriate behavior, harassment of an
+individual, or aggression toward or disparagement of classes of individuals.
+
+**Consequence**: A permanent ban from any sort of public interaction within the
+community.
+
+## Attribution
+
+This Code of Conduct is adapted from the [Contributor Covenant](https://www.contributor-covenant.org/),
+version 2.1, available at
+[v2.1](https://www.contributor-covenant.org/version/2/1/code_of_conduct.html).
+
+Community Impact Guidelines were inspired by
+[Mozilla's code of conduct enforcement ladder](https://github.com/mozilla/inclusion).
+
+For answers to common questions about this code of conduct, see the
+[Contributor Covenant FAQ](https://www.contributor-covenant.org/faq). Translations are available at
+[Contributor Covenant translations](https://www.contributor-covenant.org/translations).
+

CONTRIBUTING.md

 # Contributing to vLLM
 
-Thank you for your interest in contributing to vLLM!
-Our community is open to everyone and welcomes all kinds of contributions, no matter how small or large.
-There are several ways you can contribute to the project:
+Thank you for your interest in contributing to vLLM! Our community is open to everyone and welcomes all kinds of contributions, no matter how small or large. There are several ways you can contribute to the project:
 
 - Identify and report any issues or bugs.
-- Request or add a new model.
+- Request or add support for a new model.
 - Suggest or implement new features.
+- Improve documentation or contribute a how-to guide. 
 
-However, remember that contributions aren't just about code.
-We believe in the power of community support; thus, answering queries, assisting others, and enhancing the documentation are highly regarded and beneficial contributions.
+We also believe in the power of community support; thus, answering queries, offering PR reviews, and assisting others are also highly regarded and beneficial contributions.
 
-Finally, one of the most impactful ways to support us is by raising awareness about vLLM.
-Talk about it in your blog posts, highlighting how it's driving your incredible projects.
-Express your support on Twitter if vLLM aids you, or simply offer your appreciation by starring our repository.
+Finally, one of the most impactful ways to support us is by raising awareness about vLLM. Talk about it in your blog posts and highlight how it's driving your incredible projects. Express your support on social media if you're using vLLM, or simply offer your appreciation by starring our repository!
 
 
-## Setup for development
+## Developing
 
-### Build from source
+Depending on the kind of development you'd like to do (e.g. Python, CUDA), you can choose to build vLLM with or without compilation. Check out the [building from source](https://docs.vllm.ai/en/latest/getting_started/installation.html#build-from-source) documentation for details.
 
-```bash
-pip install -e .  # This may take several minutes.
-```
 
-### Testing
+## Testing
 
 ```bash
 pip install -r requirements-dev.txt
@@ -36,15 +29,16 @@ mypy
 # Unit tests
 pytest tests/
 ```
-**Note:** Currently, the repository does not pass the mypy tests.
+**Note:** Currently, the repository does not pass the ``mypy`` tests.
 
+## Contribution Guidelines
 
-## Contributing Guidelines
+### Issues
 
-### Issue Reporting
+If you encounter a bug or have a feature request, please [search existing issues](https://github.com/vllm-project/vllm/issues?q=is%3Aissue) first to see if it has already been reported. If not, please [file a new issue](https://github.com/vllm-project/vllm/issues/new/choose), providing as much relevant information as possible.
 
-If you encounter a bug or have a feature request, please check our issues page first to see if someone else has already reported it.
-If not, please file a new issue, providing as much relevant information as possible.
+> [!IMPORTANT]
+> If you discover a security vulnerability, please follow the instructions [here](/SECURITY.md#reporting-a-vulnerability).
 
 ### Pull Requests & Code Reviews
 
@@ -53,4 +47,4 @@ Please check the PR checklist in the [PR template](.github/PULL_REQUEST_TEMPLATE
 ### Thank You
 
 Finally, thank you for taking the time to read these guidelines and for your interest in contributing to vLLM.
-Your contributions make vLLM a great tool for everyone!
+All of your contributions help make vLLM a great tool and community for everyone!

Dockerfile

@@ -9,28 +9,31 @@ ARG CUDA_VERSION=12.4.1
 #################### BASE BUILD IMAGE ####################
 # prepare basic build environment
 FROM nvidia/cuda:${CUDA_VERSION}-devel-ubuntu20.04 AS base
-
 ARG CUDA_VERSION=12.4.1
-ARG PYTHON_VERSION=3.10
-
+ARG PYTHON_VERSION=3.12
 ENV DEBIAN_FRONTEND=noninteractive
 
+# Install Python and other dependencies
 RUN echo 'tzdata tzdata/Areas select America' | debconf-set-selections \
     && echo 'tzdata tzdata/Zones/America select Los_Angeles' | debconf-set-selections \
     && apt-get update -y \
-    && apt-get install -y ccache software-properties-common \
+    && apt-get install -y ccache software-properties-common git curl sudo \
     && add-apt-repository ppa:deadsnakes/ppa \
     && apt-get update -y \
     && apt-get install -y python${PYTHON_VERSION} python${PYTHON_VERSION}-dev python${PYTHON_VERSION}-venv \
-    && if [ "${PYTHON_VERSION}" != "3" ]; then update-alternatives --install /usr/bin/python3 python3 /usr/bin/python${PYTHON_VERSION} 1; fi \
-    && python3 --version
-
-RUN apt-get update -y \
-    && apt-get install -y git curl sudo
-
-# Install pip s.t. it will be compatible with our PYTHON_VERSION
-RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python${PYTHON_VERSION}
-RUN python3 -m pip --version
+    && update-alternatives --install /usr/bin/python3 python3 /usr/bin/python${PYTHON_VERSION} 1 \
+    && update-alternatives --set python3 /usr/bin/python${PYTHON_VERSION} \
+    && ln -sf /usr/bin/python${PYTHON_VERSION}-config /usr/bin/python3-config \
+    && curl -sS https://bootstrap.pypa.io/get-pip.py | python${PYTHON_VERSION} \
+    && python3 --version && python3 -m pip --version
+
+# Upgrade to GCC 10 to avoid https://gcc.gnu.org/bugzilla/show_bug.cgi?id=92519
+# as it was causing spam when compiling the CUTLASS kernels
+RUN apt-get install -y gcc-10 g++-10
+RUN update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-10 110 --slave /usr/bin/g++ g++ /usr/bin/g++-10
+RUN <<EOF
+gcc --version
+EOF
 
 # Workaround for https://github.com/openai/triton/issues/2507 and
 # https://github.com/pytorch/pytorch/issues/107960 -- hopefully
@@ -42,14 +45,10 @@ WORKDIR /workspace
 
 # install build and runtime dependencies
 COPY requirements-common.txt requirements-common.txt
-COPY requirements-adag.txt requirements-adag.txt
 COPY requirements-cuda.txt requirements-cuda.txt
 RUN --mount=type=cache,target=/root/.cache/pip \
     python3 -m pip install -r requirements-cuda.txt
 
-COPY requirements-mamba.txt requirements-mamba.txt
-RUN python3 -m pip install packaging
-RUN python3 -m pip install -r requirements-mamba.txt
 
 # cuda arch list used by torch
 # can be useful for both `dev` and `test`
@@ -57,32 +56,24 @@ RUN python3 -m pip install -r requirements-mamba.txt
 # see https://github.com/pytorch/pytorch/pull/123243
 ARG torch_cuda_arch_list='7.0 7.5 8.0 8.6 8.9 9.0+PTX'
 ENV TORCH_CUDA_ARCH_LIST=${torch_cuda_arch_list}
+# Override the arch list for flash-attn to reduce the binary size
+ARG vllm_fa_cmake_gpu_arches='80-real;90-real'
+ENV VLLM_FA_CMAKE_GPU_ARCHES=${vllm_fa_cmake_gpu_arches}
 #################### BASE BUILD IMAGE ####################
 
 #################### WHEEL BUILD IMAGE ####################
 FROM base AS build
 
-ARG PYTHON_VERSION=3.10
-
 # install build dependencies
 COPY requirements-build.txt requirements-build.txt
 
 RUN --mount=type=cache,target=/root/.cache/pip \
     python3 -m pip install -r requirements-build.txt
 
-# install compiler cache to speed up compilation leveraging local or remote caching
-RUN apt-get update -y && apt-get install -y ccache
-
-# files and directories related to build wheels
-COPY csrc csrc
-COPY setup.py setup.py
-COPY cmake cmake
-COPY CMakeLists.txt CMakeLists.txt
-COPY requirements-common.txt requirements-common.txt
-COPY requirements-adag.txt requirements-adag.txt
-COPY requirements-cuda.txt requirements-cuda.txt
-COPY pyproject.toml pyproject.toml
-COPY vllm vllm
+COPY . .
+ARG GIT_REPO_CHECK=0
+RUN --mount=type=bind,source=.git,target=.git \
+    if [ "$GIT_REPO_CHECK" != 0 ]; then bash tools/check_repo.sh ; fi
 
 # max jobs used by Ninja to build extensions
 ARG max_jobs=2
@@ -91,24 +82,23 @@ ENV MAX_JOBS=${max_jobs}
 ARG nvcc_threads=8
 ENV NVCC_THREADS=$nvcc_threads
 
-ARG buildkite_commit
-ENV BUILDKITE_COMMIT=${buildkite_commit}
-
 ARG USE_SCCACHE
+ARG SCCACHE_BUCKET_NAME=vllm-build-sccache
+ARG SCCACHE_REGION_NAME=us-west-2
+ARG SCCACHE_S3_NO_CREDENTIALS=0
 # if USE_SCCACHE is set, use sccache to speed up compilation
 RUN --mount=type=cache,target=/root/.cache/pip \
+    --mount=type=bind,source=.git,target=.git \
     if [ "$USE_SCCACHE" = "1" ]; then \
         echo "Installing sccache..." \
         && curl -L -o sccache.tar.gz https://github.com/mozilla/sccache/releases/download/v0.8.1/sccache-v0.8.1-x86_64-unknown-linux-musl.tar.gz \
         && tar -xzf sccache.tar.gz \
         && sudo mv sccache-v0.8.1-x86_64-unknown-linux-musl/sccache /usr/bin/sccache \
         && rm -rf sccache.tar.gz sccache-v0.8.1-x86_64-unknown-linux-musl \
-        && if [ "$CUDA_VERSION" = "11.8.0" ]; then \
-            export SCCACHE_BUCKET=vllm-build-sccache-2; \
-           else \
-            export SCCACHE_BUCKET=vllm-build-sccache; \
-           fi \
-        && export SCCACHE_REGION=us-west-2 \
+        && export SCCACHE_BUCKET=${SCCACHE_BUCKET_NAME} \
+        && export SCCACHE_REGION=${SCCACHE_REGION_NAME} \
+        && export SCCACHE_S3_NO_CREDENTIALS=${SCCACHE_S3_NO_CREDENTIALS} \
+        && export SCCACHE_IDLE_TIMEOUT=0 \
         && export CMAKE_BUILD_TYPE=Release \
         && sccache --show-stats \
         && python3 setup.py bdist_wheel --dist-dir=dist --py-limited-api=cp38 \
@@ -118,14 +108,22 @@ RUN --mount=type=cache,target=/root/.cache/pip \
 ENV CCACHE_DIR=/root/.cache/ccache
 RUN --mount=type=cache,target=/root/.cache/ccache \
     --mount=type=cache,target=/root/.cache/pip \
+    --mount=type=bind,source=.git,target=.git  \
     if [ "$USE_SCCACHE" != "1" ]; then \
         python3 setup.py bdist_wheel --dist-dir=dist --py-limited-api=cp38; \
     fi
 
-# check the size of the wheel, we cannot upload wheels larger than 100MB
+# Check the size of the wheel if RUN_WHEEL_CHECK is true
 COPY .buildkite/check-wheel-size.py check-wheel-size.py
-RUN python3 check-wheel-size.py dist
-
+# Default max size of the wheel is 250MB
+ARG VLLM_MAX_SIZE_MB=250
+ENV VLLM_MAX_SIZE_MB=$VLLM_MAX_SIZE_MB
+ARG RUN_WHEEL_CHECK=true
+RUN if [ "$RUN_WHEEL_CHECK" = "true" ]; then \
+        python3 check-wheel-size.py dist; \
+    else \
+        echo "Skipping wheel size check."; \
+    fi
 #################### EXTENSION Build IMAGE ####################
 
 #################### DEV IMAGE ####################
@@ -138,45 +136,31 @@ RUN --mount=type=cache,target=/root/.cache/pip \
     python3 -m pip install -r requirements-dev.txt
 
 #################### DEV IMAGE ####################
-#################### MAMBA Build IMAGE ####################
-FROM dev as mamba-builder
-# max jobs used for build
-ARG max_jobs=2
-ENV MAX_JOBS=${max_jobs}
-
-WORKDIR /usr/src/mamba
-
-COPY requirements-mamba.txt requirements-mamba.txt
-
-# Download the wheel or build it if a pre-compiled release doesn't exist
-RUN pip --verbose wheel -r requirements-mamba.txt \
-    --no-build-isolation --no-deps --no-cache-dir
-
-#################### MAMBA Build IMAGE ####################
-
 #################### vLLM installation IMAGE ####################
 # image with vLLM installed
-FROM nvidia/cuda:${CUDA_VERSION}-base-ubuntu20.04 AS vllm-base
+FROM nvidia/cuda:${CUDA_VERSION}-base-ubuntu22.04 AS vllm-base
 ARG CUDA_VERSION=12.4.1
-ARG PYTHON_VERSION=3.10
+ARG PYTHON_VERSION=3.12
 WORKDIR /vllm-workspace
+ENV DEBIAN_FRONTEND=noninteractive
 
+RUN PYTHON_VERSION_STR=$(echo ${PYTHON_VERSION} | sed 's/\.//g') && \
+    echo "export PYTHON_VERSION_STR=${PYTHON_VERSION_STR}" >> /etc/environment
+
+# Install Python and other dependencies
 RUN echo 'tzdata tzdata/Areas select America' | debconf-set-selections \
     && echo 'tzdata tzdata/Zones/America select Los_Angeles' | debconf-set-selections \
     && apt-get update -y \
-    && apt-get install -y ccache software-properties-common \
+    && apt-get install -y ccache software-properties-common git curl sudo vim python3-pip \
+    && apt-get install -y ffmpeg libsm6 libxext6 libgl1 \
     && add-apt-repository ppa:deadsnakes/ppa \
     && apt-get update -y \
-    && apt-get install -y python${PYTHON_VERSION} python${PYTHON_VERSION}-dev python${PYTHON_VERSION}-venv \
-    && if [ "${PYTHON_VERSION}" != "3" ]; then update-alternatives --install /usr/bin/python3 python3 /usr/bin/python${PYTHON_VERSION} 1; fi \
-    && python3 --version
-
-RUN apt-get update -y \
-    && apt-get install -y python3-pip git vim curl libibverbs-dev
-
-# Install pip s.t. it will be compatible with our PYTHON_VERSION
-RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python${PYTHON_VERSION}
-RUN python3 -m pip --version
+    && apt-get install -y python${PYTHON_VERSION} python${PYTHON_VERSION}-dev python${PYTHON_VERSION}-venv libibverbs-dev \
+    && update-alternatives --install /usr/bin/python3 python3 /usr/bin/python${PYTHON_VERSION} 1 \
+    && update-alternatives --set python3 /usr/bin/python${PYTHON_VERSION} \
+    && ln -sf /usr/bin/python${PYTHON_VERSION}-config /usr/bin/python3-config \
+    && curl -sS https://bootstrap.pypa.io/get-pip.py | python${PYTHON_VERSION} \
+    && python3 --version && python3 -m pip --version
 
 # Workaround for https://github.com/openai/triton/issues/2507 and
 # https://github.com/pytorch/pytorch/issues/107960 -- hopefully
@@ -189,12 +173,10 @@ RUN --mount=type=bind,from=build,src=/workspace/dist,target=/vllm-workspace/dist
     --mount=type=cache,target=/root/.cache/pip \
     python3 -m pip install dist/*.whl --verbose
 
-RUN --mount=type=bind,from=mamba-builder,src=/usr/src/mamba,target=/usr/src/mamba \
-    --mount=type=cache,target=/root/.cache/pip \
-    python3 -m pip install /usr/src/mamba/*.whl --no-cache-dir
-
 RUN --mount=type=cache,target=/root/.cache/pip \
-    python3 -m pip install https://github.com/flashinfer-ai/flashinfer/releases/download/v0.1.2/flashinfer-0.1.2+cu121torch2.4-cp310-cp310-linux_x86_64.whl
+    . /etc/environment && \
+    python3 -m pip install https://github.com/flashinfer-ai/flashinfer/releases/download/v0.1.6/flashinfer-0.1.6+cu121torch2.4-cp${PYTHON_VERSION_STR}-cp${PYTHON_VERSION_STR}-linux_x86_64.whl
+COPY examples examples
 #################### vLLM installation IMAGE ####################
 
 
@@ -224,7 +206,7 @@ FROM vllm-base AS vllm-openai
 
 # install additional dependencies for openai api server
 RUN --mount=type=cache,target=/root/.cache/pip \
-    pip install accelerate hf_transfer 'modelscope!=1.15.0'
+    pip install accelerate hf_transfer 'modelscope!=1.15.0' bitsandbytes>=0.44.0 timm==0.9.10
 
 ENV VLLM_USAGE_SOURCE production-docker-image
 

Dockerfile.cpu

@@ -2,37 +2,61 @@
 
 FROM ubuntu:22.04 AS cpu-test-1
 
-RUN apt-get update -y \
-    && apt-get install -y curl git wget vim numactl gcc-12 g++-12 python3 python3-pip libtcmalloc-minimal4 libnuma-dev \
+ENV CCACHE_DIR=/root/.cache/ccache
+
+ENV CMAKE_CXX_COMPILER_LAUNCHER=ccache
+
+RUN --mount=type=cache,target=/var/cache/apt \
+    apt-get update -y \
+    && apt-get install -y curl ccache git wget vim numactl gcc-12 g++-12 python3 python3-pip libtcmalloc-minimal4 libnuma-dev \
+    && apt-get install -y ffmpeg libsm6 libxext6 libgl1 \
     && update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-12 10 --slave /usr/bin/g++ g++ /usr/bin/g++-12
 
 # https://intel.github.io/intel-extension-for-pytorch/cpu/latest/tutorials/performance_tuning/tuning_guide.html
 # intel-openmp provides additional performance improvement vs. openmp
 # tcmalloc provides better memory allocation efficiency, e.g, holding memory in caches to speed up access of commonly-used objects.
-RUN pip install intel-openmp
+RUN --mount=type=cache,target=/root/.cache/pip \
+    pip install intel-openmp
 
-ENV LD_PRELOAD="/usr/lib/x86_64-linux-gnu/libtcmalloc_minimal.so.4:/usr/local/lib/libiomp5.so:$LD_PRELOAD"
+ENV LD_PRELOAD="/usr/lib/x86_64-linux-gnu/libtcmalloc_minimal.so.4:/usr/local/lib/libiomp5.so"
 
 RUN echo 'ulimit -c 0' >> ~/.bashrc
 
-RUN pip install https://intel-extension-for-pytorch.s3.amazonaws.com/ipex_dev/cpu/intel_extension_for_pytorch-2.4.0%2Bgitfbaa4bc-cp310-cp310-linux_x86_64.whl
+RUN pip install intel_extension_for_pytorch==2.4.0
 
-RUN pip install --upgrade pip \
-    && pip install wheel packaging ninja "setuptools>=49.4.0" numpy
+WORKDIR /workspace
 
-FROM cpu-test-1 AS build
+ARG PIP_EXTRA_INDEX_URL="https://download.pytorch.org/whl/cpu"
+ENV PIP_EXTRA_INDEX_URL=${PIP_EXTRA_INDEX_URL}
+RUN --mount=type=cache,target=/root/.cache/pip \
+    --mount=type=bind,src=requirements-build.txt,target=requirements-build.txt \
+    pip install --upgrade pip && \
+    pip install -r requirements-build.txt
 
-COPY ./ /workspace/vllm
+FROM cpu-test-1 AS build
 
 WORKDIR /workspace/vllm
 
-RUN pip install -v -r requirements-cpu.txt --extra-index-url https://download.pytorch.org/whl/cpu
+RUN --mount=type=cache,target=/root/.cache/pip \
+    --mount=type=bind,src=requirements-common.txt,target=requirements-common.txt \
+    --mount=type=bind,src=requirements-cpu.txt,target=requirements-cpu.txt \
+    pip install -v -r requirements-cpu.txt
+
+COPY . .
+ARG GIT_REPO_CHECK=0
+RUN --mount=type=bind,source=.git,target=.git \
+    if [ "$GIT_REPO_CHECK" != 0 ]; then bash tools/check_repo.sh ; fi
 
 # Support for building with non-AVX512 vLLM: docker build --build-arg VLLM_CPU_DISABLE_AVX512="true" ...
 ARG VLLM_CPU_DISABLE_AVX512
 ENV VLLM_CPU_DISABLE_AVX512=${VLLM_CPU_DISABLE_AVX512}
 
-RUN VLLM_TARGET_DEVICE=cpu python3 setup.py install
+RUN --mount=type=cache,target=/root/.cache/pip \
+    --mount=type=cache,target=/root/.cache/ccache \
+    --mount=type=bind,source=.git,target=.git \
+    VLLM_TARGET_DEVICE=cpu python3 setup.py bdist_wheel && \
+    pip install dist/*.whl && \
+    rm -rf dist
 
 WORKDIR /workspace/
 

Dockerfile.neuron

 # default base image
-ARG BASE_IMAGE="763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference-neuronx:2.1.1-neuronx-py310-sdk2.17.0-ubuntu20.04"
+ARG BASE_IMAGE="public.ecr.aws/neuron/pytorch-inference-neuronx:2.1.2-neuronx-py310-sdk2.20.0-ubuntu20.04"
 
 FROM $BASE_IMAGE
 
 RUN echo "Base image is $BASE_IMAGE"
 
 # Install some basic utilities
-RUN apt-get update && apt-get install python3 python3-pip -y
+RUN apt-get update && \
+    apt-get install -y \
+        git \
+        python3 \
+        python3-pip \
+        ffmpeg libsm6 libxext6 libgl1
 
 ### Mount Point ###
 # When launching the container, mount the code directory to /app
 ARG APP_MOUNT=/app
 VOLUME [ ${APP_MOUNT} ]
-WORKDIR ${APP_MOUNT}
+WORKDIR ${APP_MOUNT}/vllm
 
 RUN python3 -m pip install --upgrade pip
 RUN python3 -m pip install --no-cache-dir fastapi ninja tokenizers pandas
 RUN python3 -m pip install sentencepiece transformers==4.36.2 -U
 RUN python3 -m pip install transformers-neuronx --extra-index-url=https://pip.repos.neuron.amazonaws.com -U
-RUN python3 -m pip install --pre neuronx-cc==2.12.* --extra-index-url=https://pip.repos.neuron.amazonaws.com -U
+RUN python3 -m pip install --pre neuronx-cc==2.15.* --extra-index-url=https://pip.repos.neuron.amazonaws.com -U
 
-COPY ./vllm /app/vllm/vllm
-COPY ./setup.py /app/vllm/setup.py
-COPY ./requirements-common.txt /app/vllm/requirements-common.txt
-COPY ./requirements-neuron.txt /app/vllm/requirements-neuron.txt
+COPY . .
+ARG GIT_REPO_CHECK=0
+RUN --mount=type=bind,source=.git,target=.git \
+    if [ "$GIT_REPO_CHECK" != 0 ]; then bash tools/check_repo.sh ; fi
 
-RUN cd /app/vllm \
-    && python3 -m pip install -U -r requirements-neuron.txt
+RUN python3 -m pip install -U \
+        cmake>=3.26 ninja packaging setuptools-scm>=8 wheel jinja2 \
+        -r requirements-neuron.txt
 
 ENV VLLM_TARGET_DEVICE neuron
-RUN cd /app/vllm \
-    && pip install -e . \
-    && cd ..
+RUN --mount=type=bind,source=.git,target=.git \
+    pip install --no-build-isolation -v -e . \
 
 CMD ["/bin/bash"]

Dockerfile.openvino

@@ -4,24 +4,20 @@
 FROM ubuntu:22.04 AS dev
 
 RUN apt-get update -y && \
-    apt-get install -y python3-pip git
+    apt-get install -y \
+        git python3-pip \
+        ffmpeg libsm6 libxext6 libgl1
 WORKDIR /workspace
 
-# copy requirements
-COPY requirements-build.txt /workspace/vllm/
-COPY requirements-common.txt /workspace/vllm/
-COPY requirements-openvino.txt /workspace/vllm/
-
-COPY vllm/ /workspace/vllm/vllm
-COPY csrc/core /workspace/vllm/csrc/core
-COPY cmake/utils.cmake /workspace/vllm/cmake/
-COPY CMakeLists.txt /workspace/vllm/
-COPY setup.py /workspace/vllm/
+COPY . .
+ARG GIT_REPO_CHECK=0
+RUN --mount=type=bind,source=.git,target=.git \
+    if [ "$GIT_REPO_CHECK" != 0 ]; then bash tools/check_repo.sh ; fi
 
 # install build requirements
 RUN PIP_EXTRA_INDEX_URL="https://download.pytorch.org/whl/cpu" python3 -m pip install -r /workspace/vllm/requirements-build.txt
 # build vLLM with OpenVINO backend
-RUN PIP_EXTRA_INDEX_URL="https://download.pytorch.org/whl/cpu https://storage.openvinotoolkit.org/simple/wheels/pre-release" VLLM_TARGET_DEVICE="openvino" python3 -m pip install /workspace/vllm/
+RUN PIP_EXTRA_INDEX_URL="https://download.pytorch.org/whl/cpu" VLLM_TARGET_DEVICE="openvino" python3 -m pip install /workspace/vllm/
 
 COPY examples/ /workspace/vllm/examples
 COPY benchmarks/ /workspace/vllm/benchmarks

Dockerfile.ppc64le

@@ -2,21 +2,35 @@ FROM mambaorg/micromamba
 ARG MAMBA_DOCKERFILE_ACTIVATE=1
 USER root
 
-RUN apt-get update  -y     && apt-get install -y git wget vim numactl gcc-12 g++-12 protobuf-compiler libprotobuf-dev     && update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-12 10 --slave /usr/bin/g++ g++ /usr/bin/g++-12
+ENV PATH="/usr/local/cargo/bin:$PATH:/opt/conda/bin/"
+
+RUN apt-get update -y && apt-get install -y git wget curl vim libnuma-dev libsndfile-dev libprotobuf-dev build-essential ffmpeg libsm6 libxext6 libgl1 
 
 # Some packages in requirements-cpu are installed here
 # IBM provides optimized packages for ppc64le processors in the open-ce project for mamba
 # Currently these may not be available for venv or pip directly
-RUN micromamba install -y -n base -c https://ftp.osuosl.org/pub/open-ce/1.11.0-p10/ -c defaults     python=3.10     pytorch-cpu=2.1.2     torchvision-cpu=0.16.2    &&     micromamba clean --all --yes
+RUN micromamba install -y -n base -c https://ftp.osuosl.org/pub/open-ce/1.11.0-p10/ -c defaults python=3.10 torchvision-cpu=0.16.2 rust && micromamba clean --all --yes
 
 COPY ./ /workspace/vllm
 
 WORKDIR /workspace/vllm
+ARG GIT_REPO_CHECK=0
+RUN --mount=type=bind,source=.git,target=.git \
+    if [ "$GIT_REPO_CHECK" != 0 ]; then bash tools/check_repo.sh; fi
 
 # These packages will be in rocketce eventually
-RUN pip install -v -r requirements-cpu.txt --prefer-binary --extra-index-url https://repo.fury.io/mgiessing
+RUN --mount=type=cache,target=/root/.cache/pip  \
+    pip install -v --prefer-binary --extra-index-url https://repo.fury.io/mgiessing \
+        cmake>=3.26 ninja packaging setuptools-scm>=8 wheel jinja2 \
+        torch==2.3.1 \
+        -r requirements-cpu.txt \
+        xformers uvloop==0.20.0
+
+RUN --mount=type=bind,source=.git,target=.git \
+    VLLM_TARGET_DEVICE=cpu python3 setup.py install
+
+WORKDIR /workspace/
 
-RUN VLLM_TARGET_DEVICE=cpu python3 setup.py install
+RUN ln -s /workspace/vllm/tests && ln -s /workspace/vllm/examples && ln -s /workspace/vllm/benchmarks
 
-WORKDIR /vllm-workspace
-ENTRYPOINT ["/opt/conda/bin/python3", "-m", "vllm.entrypoints.openai.api_server"]
+ENTRYPOINT ["python3", "-m", "vllm.entrypoints.openai.api_server"]

Dockerfile.rocm

-# Default ROCm 6.1 base image
-ARG BASE_IMAGE="rocm/pytorch:rocm6.1.2_ubuntu20.04_py3.9_pytorch_staging"
+# Default ROCm 6.2 base image
+ARG BASE_IMAGE="rocm/pytorch:rocm6.2_ubuntu20.04_py3.9_pytorch_release_2.3.0"
 
 # Default ROCm ARCHes to build vLLM for.
 ARG PYTORCH_ROCM_ARCH="gfx908;gfx90a;gfx942;gfx1100"
@@ -7,18 +7,12 @@ ARG PYTORCH_ROCM_ARCH="gfx908;gfx90a;gfx942;gfx1100"
 # Whether to install CK-based flash-attention
 # If 0, will not install flash-attention
 ARG BUILD_FA="1"
-# If `TRY_FA_WHEEL=1`, we will try installing flash-attention from `FA_WHEEL_URL`
-# If this succeeds, we use the downloaded wheel and skip building flash-attention.
-# Otherwise, ROCm flash-attention from `FA_BRANCH` will be built for the
-# architectures specified in `FA_GFX_ARCHS`
-ARG TRY_FA_WHEEL="1"
-ARG FA_WHEEL_URL="https://github.com/ROCm/flash-attention/releases/download/v2.5.9post1-cktile-vllm/flash_attn-2.5.9.post1-cp39-cp39-linux_x86_64.whl"
 ARG FA_GFX_ARCHS="gfx90a;gfx942"
-ARG FA_BRANCH="23a2b1c2"
+ARG FA_BRANCH="3cea2fb"
 
 # Whether to build triton on rocm
 ARG BUILD_TRITON="1"
-ARG TRITON_BRANCH="e0fc12c"
+ARG TRITON_BRANCH="e192dba"
 
 ### Base image build stage
 FROM $BASE_IMAGE AS base
@@ -50,14 +44,17 @@ RUN python3 -m pip install --upgrade pip
 # Remove sccache so it doesn't interfere with ccache
 # TODO: implement sccache support across components
 RUN apt-get purge -y sccache; python3 -m pip uninstall -y sccache; rm -f "$(which sccache)"
-# Install torch == 2.5.0 on ROCm
-RUN case "$(ls /opt | grep -Po 'rocm-[0-9]\.[0-9]')" in \
-        *"rocm-6.1"*) \
+
+# Install torch == 2.6.0 on ROCm
+RUN --mount=type=cache,target=/root/.cache/pip \
+    case "$(ls /opt | grep -Po 'rocm-[0-9]\.[0-9]')" in \
+        *"rocm-6.2"*) \
             python3 -m pip uninstall -y torch torchvision \
-            && python3 -m pip install --no-cache-dir --pre \
-                torch==2.5.0.dev20240726 \
-                torchvision==0.20.0.dev20240726 \
-               --index-url https://download.pytorch.org/whl/nightly/rocm6.1;; \
+            && python3 -m pip install --pre \
+                torch==2.6.0.dev20240918 \
+                setuptools-scm>=8 \
+                torchvision==0.20.0.dev20240918 \
+                --extra-index-url https://download.pytorch.org/whl/nightly/rocm6.2;; \
         *) ;; esac
 
 ENV LLVM_SYMBOLIZER_PATH=/opt/rocm/llvm/bin/llvm-symbolizer
@@ -79,25 +76,18 @@ RUN cd /opt/rocm/share/amd_smi \
 ### Flash-Attention wheel build stage
 FROM base AS build_fa
 ARG BUILD_FA
-ARG TRY_FA_WHEEL
-ARG FA_WHEEL_URL
 ARG FA_GFX_ARCHS
 ARG FA_BRANCH
 # Build ROCm flash-attention wheel if `BUILD_FA = 1`
 RUN --mount=type=cache,target=${CCACHE_DIR} \
     if [ "$BUILD_FA" = "1" ]; then \
-        if [ "${TRY_FA_WHEEL}" = "1" ] && python3 -m pip install "${FA_WHEEL_URL}"; then \
-            # If a suitable wheel exists, we download it instead of building FA
-            mkdir -p /install && wget -N "${FA_WHEEL_URL}" -P /install; \
-        else \
-            mkdir -p libs \
-            && cd libs \
-            && git clone https://github.com/ROCm/flash-attention.git \
-            && cd flash-attention \
-            && git checkout "${FA_BRANCH}" \
-            && git submodule update --init \
-            && GPU_ARCHS="${FA_GFX_ARCHS}" python3 setup.py bdist_wheel --dist-dir=/install; \
-        fi; \
+        mkdir -p libs \
+        && cd libs \
+        && git clone https://github.com/ROCm/flash-attention.git \
+        && cd flash-attention \
+        && git checkout "${FA_BRANCH}" \
+        && git submodule update --init \
+        && GPU_ARCHS="${FA_GFX_ARCHS}" python3 setup.py bdist_wheel --dist-dir=/install; \
     # Create an empty directory otherwise as later build stages expect one
     else mkdir -p /install; \
     fi
@@ -112,6 +102,7 @@ RUN --mount=type=cache,target=${CCACHE_DIR} \
     if [ "$BUILD_TRITON" = "1" ]; then \
     mkdir -p libs \
     && cd libs \
+    && python3 -m pip install ninja cmake wheel pybind11 \
     && git clone https://github.com/OpenAI/triton.git \
     && cd triton \
     && git checkout "${TRITON_BRANCH}" \
@@ -126,10 +117,13 @@ RUN --mount=type=cache,target=${CCACHE_DIR} \
 FROM base AS final
 # Import the vLLM development directory from the build context
 COPY . .
+ARG GIT_REPO_CHECK=0
+RUN --mount=type=bind,source=.git,target=.git \
+    if [ "$GIT_REPO_CHECK" != 0 ]; then bash tools/check_repo.sh ; fi
 
 # Package upgrades for useful functionality or to avoid dependency issues
 RUN --mount=type=cache,target=/root/.cache/pip \
-    python3 -m pip install --upgrade numba scipy huggingface-hub[cli]
+    python3 -m pip install --upgrade numba scipy huggingface-hub[cli] pytest-shard
 
 
 # Workaround for ray >= 2.10.0
@@ -138,15 +132,9 @@ ENV RAY_EXPERIMENTAL_NOSET_ROCR_VISIBLE_DEVICES=1
 ENV TOKENIZERS_PARALLELISM=false
 
 RUN --mount=type=cache,target=${CCACHE_DIR} \
+    --mount=type=bind,source=.git,target=.git \
     --mount=type=cache,target=/root/.cache/pip \
     python3 -m pip install -Ur requirements-rocm.txt \
-    && case "$(ls /opt | grep -Po 'rocm-[0-9]\.[0-9]')" in \
-        *"rocm-6.1"*) \
-            # Bring in upgrades to HIP graph earlier than ROCm 6.2 for vLLM
-            wget -N https://github.com/ROCm/vllm/raw/fa78403/rocm_patch/libamdhip64.so.6 -P /opt/rocm/lib \
-            # Prevent interference if torch bundles its own HIP runtime
-            && rm -f "$(python3 -c 'import torch; print(torch.__path__[0])')"/lib/libamdhip64.so* || true;; \
-        *) ;; esac \
     && python3 setup.py clean --all \
     && python3 setup.py develop
 

Dockerfile.tpu

-ARG NIGHTLY_DATE="20240726"
+ARG NIGHTLY_DATE="20240828"
 ARG BASE_IMAGE="us-central1-docker.pkg.dev/tpu-pytorch-releases/docker/xla:nightly_3.10_tpuvm_$NIGHTLY_DATE"
 
 FROM $BASE_IMAGE
-WORKDIR /workspace
+WORKDIR /workspace/vllm
 
-# Install aiohttp separately to avoid build errors.
-RUN pip install aiohttp
-# Install NumPy 1 instead of NumPy 2.
-RUN pip install "numpy<2"
-# Install the TPU and Pallas dependencies.
-RUN pip install torch_xla[tpu] -f https://storage.googleapis.com/libtpu-releases/index.html
-RUN pip install torch_xla[pallas] -f https://storage.googleapis.com/jax-releases/jax_nightly_releases.html -f https://storage.googleapis.com/jax-releases/jaxlib_nightly_releases.html
+# Install some basic utilities
+RUN apt-get update && apt-get install -y \
+    git \
+    ffmpeg libsm6 libxext6 libgl1
 
-# Fix FastAPI dependence
-RUN pip install "starlette<0.38.0"
+# Install the TPU and Pallas dependencies.
+RUN --mount=type=cache,target=/root/.cache/pip \
+    python3 -m pip install torch_xla[tpu] -f https://storage.googleapis.com/libtpu-releases/index.html
+RUN --mount=type=cache,target=/root/.cache/pip \
+    python3 -m pip install torch_xla[pallas] -f https://storage.googleapis.com/jax-releases/jax_nightly_releases.html -f https://storage.googleapis.com/jax-releases/jaxlib_nightly_releases.html
 
 # Build vLLM.
-COPY . /workspace/vllm
+COPY . .
+ARG GIT_REPO_CHECK=0
+RUN --mount=type=bind,source=.git,target=.git \
+    if [ "$GIT_REPO_CHECK" != 0 ]; then bash tools/check_repo.sh; fi
+
 ENV VLLM_TARGET_DEVICE="tpu"
-RUN cd /workspace/vllm && python setup.py develop
+RUN --mount=type=cache,target=/root/.cache/pip \
+    --mount=type=bind,source=.git,target=.git \
+    python3 -m pip install \
+        cmake>=3.26 ninja packaging setuptools-scm>=8 wheel jinja2 \
+        -r requirements-tpu.txt
+RUN python3 setup.py develop
 
 CMD ["/bin/bash"]

Dockerfile.xpu

-FROM intel/oneapi-basekit:2024.1.0-devel-ubuntu20.04
+FROM intel/oneapi-basekit:2024.2.1-0-devel-ubuntu22.04 AS vllm-base
 
 RUN wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB | gpg --dearmor | tee /usr/share/keyrings/intel-oneapi-archive-keyring.gpg > /dev/null && \
     echo "deb [signed-by=/usr/share/keyrings/intel-oneapi-archive-keyring.gpg] https://apt.repos.intel.com/oneapi all main " | tee /etc/apt/sources.list.d/oneAPI.list && \
     chmod 644 /usr/share/keyrings/intel-oneapi-archive-keyring.gpg && \
-    rm /etc/apt/sources.list.d/intel-graphics.list && \
     wget -O- https://repositories.intel.com/graphics/intel-graphics.key | gpg --dearmor | tee /usr/share/keyrings/intel-graphics.gpg > /dev/null && \
     echo "deb [arch=amd64,i386 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/graphics/ubuntu jammy arc" | tee /etc/apt/sources.list.d/intel.gpu.jammy.list && \
     chmod 644 /usr/share/keyrings/intel-graphics.gpg
 
-RUN apt-get update  -y \
-&& apt-get install -y curl libicu70 lsb-release git wget vim numactl python3 python3-pip
-
-COPY ./ /workspace/vllm
+RUN apt-get update -y && \
+    apt-get install -y --no-install-recommends --fix-missing \
+    curl \
+    ffmpeg \
+    git \
+    libsndfile1 \
+    libsm6 \
+    libxext6 \
+    libgl1 \
+    lsb-release \
+    numactl \
+    python3 \
+    python3-dev \
+    python3-pip \
+    # vim \
+    wget
 
 WORKDIR /workspace/vllm
+COPY requirements-xpu.txt /workspace/vllm/requirements-xpu.txt
+COPY requirements-common.txt /workspace/vllm/requirements-common.txt
+
+RUN --mount=type=cache,target=/root/.cache/pip \
+    pip install --no-cache-dir \
+    --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/ \
+    -r requirements-xpu.txt
 
-RUN pip install -v -r requirements-xpu.txt
+COPY . .
+ARG GIT_REPO_CHECK
+RUN --mount=type=bind,source=.git,target=.git \
+    if [ "$GIT_REPO_CHECK" != 0 ]; then bash tools/check_repo.sh; fi
 
-RUN VLLM_TARGET_DEVICE=xpu python3 setup.py install
+ENV VLLM_TARGET_DEVICE=xpu
+
+RUN --mount=type=cache,target=/root/.cache/pip \
+    --mount=type=bind,source=.git,target=.git \
+    python3 setup.py install
 
 CMD ["/bin/bash"]
+
+FROM vllm-base AS vllm-openai
+
+# install additional dependencies for openai api server
+RUN --mount=type=cache,target=/root/.cache/pip \
+    pip install accelerate hf_transfer 'modelscope!=1.15.0'
+
+ENV VLLM_USAGE_SOURCE production-docker-image \
+    TRITON_XPU_PROFILE 1
+
+ENTRYPOINT ["python3", "-m", "vllm.entrypoints.openai.api_server"]

MANIFEST.in

 include LICENSE
-include requirements-adag.txt
 include requirements-common.txt
 include requirements-cuda.txt
 include requirements-rocm.txt

README.md

@@ -4,30 +4,23 @@ vLLM是一个快速且易于使用的LLM推理和服务库，使用PageAttention
 
 ## 暂不支持的官方功能
 - **量化推理**：目前支持fp16的推理和gptq,awq-int4推理，mralin的权重量化、kv-cache fp8推理方案暂不支持
-- **模块支持**：目前不支持Sliding window attention、 moe kernel模块
+- **模块支持**：目前不支持Sliding window attention
 
 
 ## 支持模型结构列表
-|     结构     |     模型      | 模型并行 | FP16 |
-| :----------: | :----------: | :------: | :--: |
-|    LlamaForCausalLM       |    LLaMA          |   Yes    | Yes  |
-|    LlamaForCausalLM       |    LLaMA-2        |   Yes    | Yes  |
-|    LlamaForCausalLM       |    LLaMA-3        |   Yes    | Yes  |
-|    LlamaForCausalLM       |    Codellama      |   Yes    | Yes  |
-|    QWenLMHeadModel        |    QWen           |   Yes    | Yes  |
-|    Qwen2ForCausalLM       |    QWen1.5        |   Yes    | Yes  |
-|    Qwen2ForCausalLM       |    CodeQwen1.5    |   Yes    | Yes  |
-|    Qwen2ForCausalLM       |    QWen2          |   Yes    | Yes  |
-|    ChatGLMModel           |    chatglm2       |   Yes    | Yes  |
-|    ChatGLMModel           |    chatglm3       |   Yes    | Yes  |
-|    BaiChuanForCausalLM    |    Baichuan-7B    |   Yes    | Yes  |
-|    BaiChuanForCausalLM    |    Baichuan2-7B   |   Yes    | Yes  |
-|    InternLMForCausalLM    |    InternLM       |   Yes    | Yes  |
-|    InternLM2ForCausalLM   |    InternLM2      |   Yes    | Yes  |
-|    LlamaForCausalLM       |    deepseek       |   Yes    | Yes  |
-|    DeepseekV2ForCausalLM  |    DeepSeek-V2    |   Yes    | Yes  |
-|    LlamaForCausalLM       |    Yi             |   Yes    | Yes  |
-|    MixtralForCausalLM     |    Mixtral-8x7B   |   Yes    | Yes  |
+| 结构 | 模型 | 模型并行 | FP16 |
+| :------: | :------: | :------: | :------: |
+| LlamaForCausalLM      | LLaMA、LLaMA-2、LLaMA-3、Codellama、deepseek、Yi | Yes | Yes |
+| QWenLMHeadModel       | QWen、Qwen-VL                                   | Yes | Yes |
+| Qwen2ForCausalLM      | QWen1.5、CodeQwen1.5、QWen2                     | Yes | Yes |
+| ChatGLMModel          | chatglm2、chatglm3、chatglm4、glm-4v-9b         | Yes | Yes |
+| BaiChuanForCausalLM   | Baichuan、Baichuan2                             | Yes | Yes |
+| BloomForCausalLM      | BLOOM                                           | Yes | Yes |
+| InternLMForCausalLM   | InternLM                                        | Yes | Yes |
+| InternLM2ForCausalLM  | InternLM2                                       | Yes | Yes |
+| DeepseekV2ForCausalLM | DeepSeek-V2                                     | Yes | Yes |
+| MixtralForCausalLM    | Mixtral-8x7B                                    | Yes | Yes |
+| TeleChat12BForCausalLM (#TelechatForCausalLM) | TeleChat-12B            | Yes | Yes |
 
 
 ## 安装
@@ -36,15 +29,16 @@ vLLM支持
 + Python 3.9.
 + Python 3.10.
 + Python 3.11.
++ Python 3.12.
 
 ### 使用源码编译方式安装
 
 #### 编译环境准备
 提供2种环境准备方式：
 
-1. 基于光源pytorch2.1.0基础镜像环境：镜像下载地址：[https://sourcefind.cn/#/image/dcu/pytorch](https://sourcefind.cn/#/image/dcu/pytorch)，根据pytorch2.1.0、python、dtk及系统下载对应的镜像版本。
+1. 基于光源pytorch2.3.0基础镜像环境：镜像下载地址：[https://sourcefind.cn/#/image/dcu/pytorch](https://sourcefind.cn/#/image/dcu/pytorch)，根据pytorch2.1.0、python、dtk及系统下载对应的镜像版本。
 
-2. 基于现有python环境：安装pytorch2.1.0，pytorch whl包下载目录：[https://cancon.hpccube.com:65024/4/main/pytorch](https://cancon.hpccube.com:65024/4/main/pytorch)，根据python、dtk版本,下载对应pytorch2.1.0的whl包。安装命令如下：
+2. 基于现有python环境：安装pytorch2.3.0，pytorch whl包下载目录：[https://cancon.hpccube.com:65024/4/main/pytorch](https://cancon.hpccube.com:65024/4/main/pytorch)，根据python、dtk版本,下载对应pytorch2.1.0的whl包。安装命令如下：
 ```shell
 pip install torch* (下载的torch的whl包)
 pip install setuptools wheel
@@ -70,9 +64,9 @@ VLLM_INSTALL_PUNICA_KERNELS=1 python3 setup.py install
 ```
 
 #### 运行基础环境准备
-1、使用上面基于光源pytorch2.1.0基础镜像环境
+1、使用上面基于光源pytorch2.3.0基础镜像环境
 
-2、根据pytorch2.1.0、python、dtk及系统下载对应的依赖包：
+2、根据pytorch2.3.0、python、dtk及系统下载对应的依赖包：
 - triton:[https://cancon.hpccube.com:65024/4/main/triton](https://cancon.hpccube.com:65024/4/main/triton/)
 - xformers:[https://cancon.hpccube.com:65024/4/main/xformers](https://cancon.hpccube.com:65024/4/main/xformers)
 - flash_attn: [https://cancon.hpccube.com:65024/4/main/flash_attn](https://cancon.hpccube.com:65024/4/main/flash_attn)
@@ -82,7 +76,7 @@ VLLM_INSTALL_PUNICA_KERNELS=1 python3 setup.py install
 + 若使用 pip install 下载安装过慢，可添加源：-i https://pypi.tuna.tsinghua.edu.cn/simple/
 
 ## 验证
-- python -c "import vllm; print(vllm.\_\_version__)"，版本号与官方版本同步，查询该软件的版本号，例如0.5.4；
+- python -c "import vllm; print(vllm.\_\_version__)"，版本号与官方版本同步，查询该软件的版本号，例如0.6.3.post1；
 
 ## Known Issue
 - 无

README_ORIGIN.md

@@ -10,13 +10,14 @@ Easy, fast, and cheap LLM serving for everyone
 </h3>
 
 <p align="center">
-| <a href="https://docs.vllm.ai"><b>Documentation</b></a> | <a href="https://vllm.ai"><b>Blog</b></a> | <a href="https://arxiv.org/abs/2309.06180"><b>Paper</b></a> | <a href="https://discord.gg/jz7wjKhh6g"><b>Discord</b></a> |
-
+| <a href="https://docs.vllm.ai"><b>Documentation</b></a> | <a href="https://vllm.ai"><b>Blog</b></a> | <a href="https://arxiv.org/abs/2309.06180"><b>Paper</b></a> | <a href="https://discord.gg/jz7wjKhh6g"><b>Discord</b></a> | <a href="https://x.com/vllm_project"><b>Twitter/X</b></a> | <a href="https://slack.vllm.ai"><b>Developer Slack</b></a> |
 </p>
 
----
 
 *Latest News* 🔥
+- [2024/10] We have just created a developer slack ([slack.vllm.ai](https://slack.vllm.ai)) focusing on coordinating contributions and discussing features. Please feel free to join us there! 
+- [2024/10] Ray Summit 2024 held a special track for vLLM! Please find the opening talk slides from the vLLM team [here](https://docs.google.com/presentation/d/1B_KQxpHBTRa_mDF-tR6i8rWdOU5QoTZNcEg2MKZxEHM/edit?usp=sharing). Learn more from the [talks](https://raysummit.anyscale.com/flow/anyscale/raysummit2024/landing/page/sessioncatalog?tab.day=20241001&search.sessiontracks=1719251906298001uzJ2) from other vLLM contributors and users!
+- [2024/09] We hosted [the sixth vLLM meetup](https://lu.ma/87q3nvnh) with NVIDIA! Please find the meetup slides [here](https://docs.google.com/presentation/d/1wrLGwytQfaOTd5wCGSPNhoaW3nq0E-9wqyP7ny93xRs/edit?usp=sharing).
 - [2024/07] We hosted [the fifth vLLM meetup](https://lu.ma/lp0gyjqr) with AWS! Please find the meetup slides [here](https://docs.google.com/presentation/d/1RgUD8aCfcHocghoP3zmXzck9vX3RCI9yfUAB2Bbcl4Y/edit?usp=sharing).
 - [2024/07] In partnership with Meta, vLLM officially supports Llama 3.1 with FP8 quantization and pipeline parallelism! Please check out our blog post [here](https://blog.vllm.ai/2024/07/23/llama31.html).
 - [2024/06] We hosted [the fourth vLLM meetup](https://lu.ma/agivllm) with Cloudflare and BentoML! Please find the meetup slides [here](https://docs.google.com/presentation/d/1iJ8o7V2bQEi0BFEljLTwc5G1S10_Rhv3beed5oB0NJ4/edit?usp=sharing).
@@ -36,10 +37,12 @@ vLLM is fast with:
 - Efficient management of attention key and value memory with **PagedAttention**
 - Continuous batching of incoming requests
 - Fast model execution with CUDA/HIP graph
-- Quantization: [GPTQ](https://arxiv.org/abs/2210.17323), [AWQ](https://arxiv.org/abs/2306.00978), [SqueezeLLM](https://arxiv.org/abs/2306.07629), FP8 KV Cache
-- Optimized CUDA kernels
+- Quantizations: [GPTQ](https://arxiv.org/abs/2210.17323), [AWQ](https://arxiv.org/abs/2306.00978), INT4, INT8, and FP8.
+- Optimized CUDA kernels, including integration with FlashAttention and FlashInfer.
+- Speculative decoding
+- Chunked prefill
 
-**Performance benchmark**: We include a [performance benchmark](https://buildkite.com/vllm/performance-benchmark/builds/4068) that compares the performance of vllm against other LLM serving engines ([TensorRT-LLM](https://github.com/NVIDIA/TensorRT-LLM), [text-generation-inference](https://github.com/huggingface/text-generation-inference) and [lmdeploy](https://github.com/InternLM/lmdeploy)).
+**Performance benchmark**: We include a performance benchmark at the end of [our blog post](https://blog.vllm.ai/2024/09/05/perf-update.html). It compares the performance of vLLM against other LLM serving engines ([TensorRT-LLM](https://github.com/NVIDIA/TensorRT-LLM), [SGLang](https://github.com/sgl-project/sglang) and [LMDeploy](https://github.com/InternLM/lmdeploy)). The implementation is under [nightly-benchmarks folder](.buildkite/nightly-benchmarks/) and you can [reproduce](https://github.com/vllm-project/vllm/issues/8176) this benchmark using our one-click runnable script. 
 
 vLLM is flexible and easy to use with:
 
@@ -48,20 +51,21 @@ vLLM is flexible and easy to use with:
 - Tensor parallelism and pipeline parallelism support for distributed inference
 - Streaming outputs
 - OpenAI-compatible API server
-- Support NVIDIA GPUs, AMD CPUs and GPUs, Intel CPUs and GPUs, PowerPC CPUs
-- (Experimental) Prefix caching support
-- (Experimental) Multi-lora support
+- Support NVIDIA GPUs, AMD CPUs and GPUs, Intel CPUs and GPUs, PowerPC CPUs, TPU, and AWS Neuron.
+- Prefix caching support
+- Multi-lora support
 
 vLLM seamlessly supports most popular open-source models on HuggingFace, including:
 - Transformer-like LLMs (e.g., Llama)
 - Mixture-of-Expert LLMs (e.g., Mixtral)
+- Embedding Models (e.g. E5-Mistral)
 - Multi-modal LLMs (e.g., LLaVA)
 
 Find the full list of supported models [here](https://docs.vllm.ai/en/latest/models/supported_models.html).
 
 ## Getting Started
 
-Install vLLM with pip or [from source](https://vllm.readthedocs.io/en/latest/getting_started/installation.html#build-from-source):
+Install vLLM with `pip` or [from source](https://vllm.readthedocs.io/en/latest/getting_started/installation.html#build-from-source):
 
 ```bash
 pip install vllm
@@ -99,6 +103,7 @@ vLLM is a community project. Our compute resources for development and testing a
 - Roblox
 - RunPod
 - Sequoia Capital
+- Skywork AI
 - Trainy
 - UC Berkeley
 - UC San Diego
@@ -116,4 +121,12 @@ If you use vLLM for your research, please cite our [paper](https://arxiv.org/abs
   booktitle={Proceedings of the ACM SIGOPS 29th Symposium on Operating Systems Principles},
   year={2023}
 }
-```
\ No newline at end of file
+```
+
+## Contact Us
+
+* For technical questions and feature requests, please use Github issues or discussions.
+* For discussing with fellow users, please use Discord.
+* For coordinating contributions and development, please use Slack.
+* For security disclosures, please use Github's security advisory feature.
+* For collaborations and partnerships, please contact us at vllm-questions AT lists.berkeley.edu.
\ No newline at end of file